Our Blog


Thresholds and Balance in our DFS Trends Tool

This is my emergency piece. It’s the backup post that I’ve written in anticipation of the day when I try to write another article and the idea just isn’t coming together. If that happens, I will post this piece instead.

So if you’re reading this sentence right now . . .

This is the 61st installment of The Labyrinthian, a series dedicated to exploring random fields of knowledge in order to give you unordinary theoretical, philosophical, strategic, and/or often rambling guidance on daily fantasy sports. Consult the introductory piece to the series for further explanation.

Our DFS Trends Tool

Shall I spam you now? — or later? Let’s just get this over with.

For an unparalleled DFS edge, try our free Trends tool, through which you can access our massive database of advanced data and leverage our premium exclusive metrics, such as Upside, Consistency, and Plus/Minus.

I love our Trends tool. I haven’t bothered actually to verify what I’m about to say — because I’m writing this piece in a hurry — because it’s a f*cking emergency piece — but I believe that I’ve actively used the Trends tool in at least a quarter of my Labyrinthian articles. Probably more.

We all know that I’m fond of quoting myself. It’s my greatest talent, other than quoting other people. Anyway, here’s something that I’ve said previously about the tools we offer at FantasyLabs:

I think of the Player Models as the daily equivalent of giving a man a fish. And, to finish the analogy, the Trends tool is the equivalent of giving a man a big juicy steak.

I could quote the rest of that shtick, but I’ve ‘entertained’ you enough.

How to Build Trends

As I write this, Cleveland outfielder Tyler Naquin has the most Pro Trends on DraftKings. He has 11. As a point of reference, the six batters who trail him with 10 Pro Trends are David Ortiz, Jay Bruce, Chris Young, Salvador Perez, Carlos Santana, and Lonnie Chisenhall. There’s definitely some potential in that group — but what is Naquin’s potential?

To answer this question, we should go to the Trends tool. But what then?

Let’s do what lots of people do: Let’s identify the factors that really stand out — the factors that make Naquin what he is in this slate — and then let’s build a trend based on those factors.

What’s notable about Naquin?

  • 11 Pro Trends: That’s why we’re here in the first place.
  • No. 8 Hitter: That’s not ideal.
  • Distance Differential (ft) of +49: That’s outstanding.

That’s probably enough to go on. So let’s build this trend. In general, when a guy has at least 10 Pro Trends, a spot in the bottom half of the order, and a Distance Differential of at least +40, how does he do?

With a Consistency of 48.3 percent, such players have averaged a +2.15 Plus/Minus.

Pro Trends, Consistency, Plus/Minus, and other premium exclusive metrics are accessible via our free Ratings tool.

This trend looks pretty good, right?

Whoever Built That Trend Is a Moron

The trend might ‘look’ good, but that’s not a good trend. For one, the sample of only 29 batters is much too small. More importantly, this trend sucks because it is constructed through thresholds instead of balanced data ranges.

  • When we screen for batters with at least 10 Pro Trends, our sample of past results will include a number of batters with 14 and 15 Pro Trends. How comparable are they, really, to Naquin?
  • When we screen for batters in the second half of the lineup, we will end up seeing some guys who bat sixth. How similar can they be to a guy hitting eighth?
  • When we screen for batters who are crushing their yearly batted-ball distance averages by at least 40 feet, we might see some guys in the data set who exceeded their yearly averages by 80 feet. Should they really be lumped into the same group with Naquin?

As I said earlier, whoever built that trend is a moron. It’s doubtful that the batters who match for this trend are actually a lot like Naquin. The trend risks being unrepresentative. And if it’s not representative, what good is it?

Is Naquin an Outlier?

In Malcolm Gladwell’s Outliers, he notes the importance of thresholds.

  • If a person is born in Canada before a certain month of the year, that person’s odds of becoming a professional hockey player are much better than they otherwise would be.
  • If a person devotes 10,000 hours to learning, practicing, and mastering a craft or skill, that person’s odds of becoming incredibly successful in that field are greatly increased.
  • If a person is fairly intelligent but is by no means a genius, then that person is still smart enough to be an accomplished thinker, researcher, and even winner of the Nobel Prize.

One can become an outlier simply by crossing thresholds.

The moronic trend above might be less moronic (and maybe even reasonable) if one wants to get a sense of Naquin’s Upside — if we want to know how he might do if he were really just a little bit better than he actually is.

Such a trend, created with thresholds, might give us a clue as to what Naquin might look like if he were an outlier.

So I suppose that threshold trends might actually be good for something.

Let’s Not Get Carried Away

Of course, because they are less representative than they could be, they might be worth nothing. It’s very possible that, in aiming high, the threshold trend falls short due to its lack of accuracy and precision. This is a very underappreciated concern.

But the real problem with threshold trends is that most people don’t use them to gauge potential ‘outlieriness.’ They use these trends believing that they provide an accurate representation of what, on average, should be expected from the players who inspired the trends.

Sometimes, the players actually do live up to or exceed such trends — because outliers and Black Swans do exist — but, in the aggregate, they very often don’t.

A lot of people create trends incorrectly.

What’s the Right Way to Build a Trend?

I’m not going to say that it’s the ‘right’ way — because each trend can serve a function if used properly — but a better way to build trends is with balance.

For instance, given that Naquin has 11 Pro Trends, it might be best to screen for players with anywhere from nine to 13 Pro Trends. In doing this, we’ll eliminate from the sample the dissimilar players with 14 and 15 Pro Trends, and we’ll put Naquin pretty close to the middle of the sample.

Now, it’s true that in the sample we will probably find more players with nine and 10 Pro Trends than with 12 and 13 Pro Trends — players with more Pro Trends just tend to be rarer — and as a result the sample might be skewed downward. I think that this is fine for a couple of reasons:

  1. If we are going to err, it’s better to be conservative, and balanced trends tend to be more conservative than the threshold trends. By creating a balanced range, we won’t create a trend that gives us unrealistic expectations of Upside. And, at a minimum, we will create a trend that is more accurate and precise. That on its own is worth a lot.
  2. In general, the extent to which a balanced trend is skewed is nothing compared to the extent to which a threshold trend is skewed. In the example of Naquin, the players with 12 and 13 Pro Trends counterweigh the players with nine and 10 Pro Trends (in the balanced trend) much more than those with 10 Pro Trends counterweigh those with 12, 13, 14, and 15 Pro Trends (in the threshold trend). As the name suggests, the balanced trend is less extreme.

If you weren’t convinced earlier that balanced trends are generally better (or more functional) than threshold trends, I hope that you’re convinced now.

Let’s Bring This Party to an End

What would a balanced trend look like for Naquin? Here’s one possibility:

  • Pro Trends: Nine to 13
  • Lineup Order: Seven to Nine
  • Distance Differential (ft) of +49: +29 to +69

And if we create this trend, what do we see? On a sample of 45 batters, we get a Plus/Minus of +3.24 and a Consistency of 60 percent with a sample of 45 batters.

In every way imaginable, this trend is better than the previous one. It doesn’t always work out that way — not always does the balanced trend yield a higher Plus/Minus, Consistency, and sample size — but more often than not it gives you a much better sense of what you’re likely to get.

With Naquin, what you’re likely to get is something you’ll probably like: 60 percent of the time, this trend works every time.

Hopefully Naquin doesn’t finish the night smelling like Bigfoot’s d*ck.

———

The Labyrinthian: 2016, 61

Previous installments of The Labyrinthian can be accessed via my author page. If you have suggestions on material I should know about or even write about in a future Labyrinthian, please contact me via email, [email protected], or Twitter @MattFtheOracle.

This is my emergency piece. It’s the backup post that I’ve written in anticipation of the day when I try to write another article and the idea just isn’t coming together. If that happens, I will post this piece instead.

So if you’re reading this sentence right now . . .

This is the 61st installment of The Labyrinthian, a series dedicated to exploring random fields of knowledge in order to give you unordinary theoretical, philosophical, strategic, and/or often rambling guidance on daily fantasy sports. Consult the introductory piece to the series for further explanation.

Our DFS Trends Tool

Shall I spam you now? — or later? Let’s just get this over with.

For an unparalleled DFS edge, try our free Trends tool, through which you can access our massive database of advanced data and leverage our premium exclusive metrics, such as Upside, Consistency, and Plus/Minus.

I love our Trends tool. I haven’t bothered actually to verify what I’m about to say — because I’m writing this piece in a hurry — because it’s a f*cking emergency piece — but I believe that I’ve actively used the Trends tool in at least a quarter of my Labyrinthian articles. Probably more.

We all know that I’m fond of quoting myself. It’s my greatest talent, other than quoting other people. Anyway, here’s something that I’ve said previously about the tools we offer at FantasyLabs:

I think of the Player Models as the daily equivalent of giving a man a fish. And, to finish the analogy, the Trends tool is the equivalent of giving a man a big juicy steak.

I could quote the rest of that shtick, but I’ve ‘entertained’ you enough.

How to Build Trends

As I write this, Cleveland outfielder Tyler Naquin has the most Pro Trends on DraftKings. He has 11. As a point of reference, the six batters who trail him with 10 Pro Trends are David Ortiz, Jay Bruce, Chris Young, Salvador Perez, Carlos Santana, and Lonnie Chisenhall. There’s definitely some potential in that group — but what is Naquin’s potential?

To answer this question, we should go to the Trends tool. But what then?

Let’s do what lots of people do: Let’s identify the factors that really stand out — the factors that make Naquin what he is in this slate — and then let’s build a trend based on those factors.

What’s notable about Naquin?

  • 11 Pro Trends: That’s why we’re here in the first place.
  • No. 8 Hitter: That’s not ideal.
  • Distance Differential (ft) of +49: That’s outstanding.

That’s probably enough to go on. So let’s build this trend. In general, when a guy has at least 10 Pro Trends, a spot in the bottom half of the order, and a Distance Differential of at least +40, how does he do?

With a Consistency of 48.3 percent, such players have averaged a +2.15 Plus/Minus.

Pro Trends, Consistency, Plus/Minus, and other premium exclusive metrics are accessible via our free Ratings tool.

This trend looks pretty good, right?

Whoever Built That Trend Is a Moron

The trend might ‘look’ good, but that’s not a good trend. For one, the sample of only 29 batters is much too small. More importantly, this trend sucks because it is constructed through thresholds instead of balanced data ranges.

  • When we screen for batters with at least 10 Pro Trends, our sample of past results will include a number of batters with 14 and 15 Pro Trends. How comparable are they, really, to Naquin?
  • When we screen for batters in the second half of the lineup, we will end up seeing some guys who bat sixth. How similar can they be to a guy hitting eighth?
  • When we screen for batters who are crushing their yearly batted-ball distance averages by at least 40 feet, we might see some guys in the data set who exceeded their yearly averages by 80 feet. Should they really be lumped into the same group with Naquin?

As I said earlier, whoever built that trend is a moron. It’s doubtful that the batters who match for this trend are actually a lot like Naquin. The trend risks being unrepresentative. And if it’s not representative, what good is it?

Is Naquin an Outlier?

In Malcolm Gladwell’s Outliers, he notes the importance of thresholds.

  • If a person is born in Canada before a certain month of the year, that person’s odds of becoming a professional hockey player are much better than they otherwise would be.
  • If a person devotes 10,000 hours to learning, practicing, and mastering a craft or skill, that person’s odds of becoming incredibly successful in that field are greatly increased.
  • If a person is fairly intelligent but is by no means a genius, then that person is still smart enough to be an accomplished thinker, researcher, and even winner of the Nobel Prize.

One can become an outlier simply by crossing thresholds.

The moronic trend above might be less moronic (and maybe even reasonable) if one wants to get a sense of Naquin’s Upside — if we want to know how he might do if he were really just a little bit better than he actually is.

Such a trend, created with thresholds, might give us a clue as to what Naquin might look like if he were an outlier.

So I suppose that threshold trends might actually be good for something.

Let’s Not Get Carried Away

Of course, because they are less representative than they could be, they might be worth nothing. It’s very possible that, in aiming high, the threshold trend falls short due to its lack of accuracy and precision. This is a very underappreciated concern.

But the real problem with threshold trends is that most people don’t use them to gauge potential ‘outlieriness.’ They use these trends believing that they provide an accurate representation of what, on average, should be expected from the players who inspired the trends.

Sometimes, the players actually do live up to or exceed such trends — because outliers and Black Swans do exist — but, in the aggregate, they very often don’t.

A lot of people create trends incorrectly.

What’s the Right Way to Build a Trend?

I’m not going to say that it’s the ‘right’ way — because each trend can serve a function if used properly — but a better way to build trends is with balance.

For instance, given that Naquin has 11 Pro Trends, it might be best to screen for players with anywhere from nine to 13 Pro Trends. In doing this, we’ll eliminate from the sample the dissimilar players with 14 and 15 Pro Trends, and we’ll put Naquin pretty close to the middle of the sample.

Now, it’s true that in the sample we will probably find more players with nine and 10 Pro Trends than with 12 and 13 Pro Trends — players with more Pro Trends just tend to be rarer — and as a result the sample might be skewed downward. I think that this is fine for a couple of reasons:

  1. If we are going to err, it’s better to be conservative, and balanced trends tend to be more conservative than the threshold trends. By creating a balanced range, we won’t create a trend that gives us unrealistic expectations of Upside. And, at a minimum, we will create a trend that is more accurate and precise. That on its own is worth a lot.
  2. In general, the extent to which a balanced trend is skewed is nothing compared to the extent to which a threshold trend is skewed. In the example of Naquin, the players with 12 and 13 Pro Trends counterweigh the players with nine and 10 Pro Trends (in the balanced trend) much more than those with 10 Pro Trends counterweigh those with 12, 13, 14, and 15 Pro Trends (in the threshold trend). As the name suggests, the balanced trend is less extreme.

If you weren’t convinced earlier that balanced trends are generally better (or more functional) than threshold trends, I hope that you’re convinced now.

Let’s Bring This Party to an End

What would a balanced trend look like for Naquin? Here’s one possibility:

  • Pro Trends: Nine to 13
  • Lineup Order: Seven to Nine
  • Distance Differential (ft) of +49: +29 to +69

And if we create this trend, what do we see? On a sample of 45 batters, we get a Plus/Minus of +3.24 and a Consistency of 60 percent with a sample of 45 batters.

In every way imaginable, this trend is better than the previous one. It doesn’t always work out that way — not always does the balanced trend yield a higher Plus/Minus, Consistency, and sample size — but more often than not it gives you a much better sense of what you’re likely to get.

With Naquin, what you’re likely to get is something you’ll probably like: 60 percent of the time, this trend works every time.

Hopefully Naquin doesn’t finish the night smelling like Bigfoot’s d*ck.

———

The Labyrinthian: 2016, 61

Previous installments of The Labyrinthian can be accessed via my author page. If you have suggestions on material I should know about or even write about in a future Labyrinthian, please contact me via email, [email protected], or Twitter @MattFtheOracle.

About the Author

Matthew Freedman is the Editor-in-Chief of FantasyLabs. The only edge he has in anything is his knowledge of '90s music.